Attention computes the dependency between representations, and it encourages model to focus on important selective features. Attention-based models, such as Transformer graph attention network (GAT), are widely utilized for sequential data graph-structured data. This paper suggests a new interpretation generalized structure of in GAT. For GAT, we derive that is product two parts: 1) RBF kernel ...

The stable spline (SS) kernel and the diagonal correlated (DC) kernel are two kernels that have been applied and studied extensively for kernel-based regularized LTI system identification. In this note, we show that similar to the derivation of the SS kernel, the continuous-time DC kernel can be derived by applying the same “stable” coordinate change to a “generalized” first-order spline kernel...

2 Graph kernels 2 2.1 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.2 The Spectrum Kernel . . . . . . . . . . . . . . . . . . . . . . . . 2 2.3 The Tanimoto Kernel . . . . . . . . . . . . . . . . . . . . . . . . 3 2.4 The MinMax Kernel . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.5 The Marginalized Kernel . . . . . . . . . . . . . . . . . . . . . . . 3 2.6 ...